import torch
#
# torch.cat((x1, self.branch2(x2)), dim=1)
# torch.cat((self.branch1(x), self.branch2(x)), dim=1)
# torch.cat((x_ch0, x_ch1, x_ch2), 1)
# torch.cat(outputs, 1)
# torch.cat([            self.expand1x1_activation(self.expand1x1(x)),           self.expand3x3_activation(self.expand3x3(x))        ], 1)
# torch.cat(res, dim=1)
# torch.cat(inputs, 1)
# torch.cat(features, 1)
# torch.cat((x_ch0, x_ch1, x_ch2), 1)
# torch.cat(outputs, 1)
# torch.cat(outputs, 1)
# torch.cat(outputs, 1)
# torch.cat(outputs, 1)
# torch.cat(branch3x3, 1)
# torch.cat(branch3x3dbl, 1)
# torch.cat(outputs, 1)
# torch.cat(        (torch.tensor([orig_pre_nms_top_n], dtype=num_anchors.dtype),         num_anchors), 0).to(torch.int32)).to(num_anchors.dtype)
# torch.cat(anchors_per_image) for anchors_per_image in anchors]
# torch.cat(box_cls_flattened, dim=1).flatten(0, -2)
# torch.cat(box_regression_flattened, dim=1).reshape(-1, 4)
# torch.cat(r, dim=1)
# torch.cat(levels, 0)
# torch.cat(sampled_pos_inds, dim=0)).squeeze(1)
# torch.cat(sampled_neg_inds, dim=0)).squeeze(1)
# torch.cat([sampled_pos_inds, sampled_neg_inds], dim=0)
# torch.cat(labels, dim=0)
# torch.cat(regression_targets, dim=0)
# torch.cat(labels, dim=0)
# torch.cat(regression_targets, dim=0)
# torch.cat(labels)
# torch.cat([matched_idxs[:, None], boxes], dim=1)
# torch.cat(labels, dim=0)
# torch.cat(mask_targets, dim=0)
# torch.cat((xy_preds.to(dtype=torch.float32),                              xy_preds_i.unsqueeze(0).to(dtype=torch.float32)), 0)
# torch.cat((end_scores.to(dtype=torch.float32),                                end_scores_i.to(dtype=torch.float32).unsqueeze(0)), 0)
# torch.cat(heatmaps, dim=0)
# torch.cat(valid, dim=0).to(dtype=torch.uint8)
# torch.cat((w, one)))
# torch.cat((h, one)))
# torch.cat((box[0].unsqueeze(0), zero)))
# torch.cat((box[2].unsqueeze(0) + one, im_w.unsqueeze(0))))
# torch.cat((box[1].unsqueeze(0), zero)))
# torch.cat((box[3].unsqueeze(0) + one, im_h.unsqueeze(0))))
# torch.cat((zeros_y0,                          unpaded_im_mask.to(dtype=torch.float32),                          zeros_y1), 0)[0:im_h, :]
# torch.cat((zeros_x0,                         concat_0,                         zeros_x1), 1)[:, :im_w]
# torch.cat((res_append, mask_res))
# torch.cat((proposal, gt_box))
# torch.cat((targets_dx, targets_dy, targets_dw, targets_dh), dim=1)
# torch.cat(reference_boxes, dim=0)
# torch.cat(proposals, dim=0)
# torch.cat(boxes, dim=0)